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| from .parts import * | |
| class Dinov2(nn.Module): | |
| def __init__(self, n_channels, n_classes, bilinear=False): | |
| super(Dinov2, self).__init__() | |
| self.n_channels = n_channels | |
| self.n_classes = n_classes | |
| self.bilinear = bilinear | |
| self.inc = (DoubleConv(n_channels, 64)) | |
| self.down1 = (Down(64, 128)) | |
| self.down2 = (Down(128, 256)) | |
| self.down3 = (Down(256, 512)) | |
| factor = 2 if bilinear else 1 | |
| self.down4 = (Down(512, 1024 // factor)) | |
| self.up1 = (Up(1024, 512 // factor, bilinear)) | |
| self.up2 = (Up(512, 256 // factor, bilinear)) | |
| self.up3 = (Up(256, 128 // factor, bilinear)) | |
| self.up4 = (Up(128, 64, bilinear)) | |
| self.outc = (OutConv(64, n_classes)) | |
| def forward(self, x): | |
| x1 = self.inc(x) | |
| x2 = self.down1(x1) | |
| x3 = self.down2(x2) | |
| x4 = self.down3(x3) | |
| x5 = self.down4(x4) | |
| x = self.up1(x5, x4) | |
| x = self.up2(x, x3) | |
| x = self.up3(x, x2) | |
| x = self.up4(x, x1) | |
| logits = self.outc(x) | |
| return logits | |
| def use_checkpointing(self): | |
| self.inc = torch.utils.checkpoint(self.inc) | |
| self.down1 = torch.utils.checkpoint(self.down1) | |
| self.down2 = torch.utils.checkpoint(self.down2) | |
| self.down3 = torch.utils.checkpoint(self.down3) | |
| self.down4 = torch.utils.checkpoint(self.down4) | |
| self.up1 = torch.utils.checkpoint(self.up1) | |
| self.up2 = torch.utils.checkpoint(self.up2) | |
| self.up3 = torch.utils.checkpoint(self.up3) | |
| self.up4 = torch.utils.checkpoint(self.up4) | |
| self.outc = torch.utils.checkpoint(self.outc) |